Flexible mean and dispersion function estimation in extended generalized additive models

I. Gijbels, I. Prosdocimi

Research output: Contribution to journalArticlepeer-review

4 Citations (SciVal)


Real data may expose a larger (or smaller) variability than assumed in an exponential family modeling, the basis of Generalized linear models and additive models. To analyze such data, smooth estimation of the mean and the dispersion function has been introduced in extended generalized additive models using Psplines techniques. This methodology is further explored here by allowing for the modeling of some of the covariates parametrically and some nonparametrically. The main contribution in this article is a simulation study investigating the finite-sample performance of the P-spline estimation technique in these extended models, including comparisons with a standard generalized additive modeling approach, as well as with a hierarchical modeling approach.

Original languageEnglish
Pages (from-to)3259-3277
Number of pages19
JournalCommunications in Statistics - Theory and Methods
Issue number16-17
Early online date25 Jul 2012
Publication statusPublished - 2012


  • Additive modeling
  • Dispersion function
  • Double exponential family
  • Mean function
  • Nonparametric estimation
  • P-splines approximation


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